Learn how to model social and economic networks and their impact on human behavior. How do networks form, why do they exhibit certain patterns, and how does their structure impact diffusion, learning, and other behaviors? We will bring together models and techniques from economics, sociology, math, physics, statistics and computer science to answer these questions.
The course begins with some empirical background on social and economic networks, and an overview of concepts used to describe and measure networks. Next, we will cover a set of models of how networks form, including random network models as well as strategic formation models, and some hybrids. We will then discuss a series of models of how networks impact behavior, including contagion, diffusion, learning, and peer influences.
You can find a more detailed syllabus here: http://web.stanford.edu/~jacksonm/Networks-Online-Syllabus.pdf
You can find a short introductory videao here: http://web.stanford.edu/~jacksonm/Intro_Networks.mp4

Taught By

Matthew O. Jackson

Professor

Transcript

Hello, welcome. I was just working with some data from a project using network analysis to understand financial contagions, more on that in a minute. Let me begin by introducing myself. I'm Matthew Jackson. What I'm really here to tell you about is an exciting new MOOC Massive Online Open Course. And it's a course on analysis and modelling of social and economic networks. The course is designed primarily for people who might be using network analysis in research. And so, it's aimed at at a Masters to PhD level, with some extra bits for people who are really interested. It should be easily accessible for advanced undergraduates. It's partly based on a PhD course that I've been teaching here at Stanford. And the lectures will be at two different levels, they'll be basic set of lectures that make up the bulk of the course. As well as some extra advance lectures that provide technical details for those who really want to immerse themselves in the subject. Let us take a quick peek at some of the types of questions that will be analyzing. So here is a figure from research I've been doing with two of my former students. Matt Elliott and Ben Golub on understanding financial contagions. It shows the amount of sovereign debt of each of the six European countries that's held inside another country. And we're using some of the modeling techniques that we'll explore in this course to understand how a shock or default in one country might spread and impact others. The next figure depicts friendships among high-school students in one of the high-schools in what's known as the Add Health data set. Nodes are coded by race, and you can see this network exhibits what's known homophily. Students are strongly segregated by race. How can we measure and explain the formation of this network? What's the impact on learning and communication of the segregation in such a network? So there's lots of interesting questions there. This third figure is another fascinating one. It depicts the marriages among 16 major families in 15th century Florence. This was a period during which the Medici rose to prominence and some of the key marriages here were engineered by Cosimo de' Medici. So how do we measure the positions of different families? Can this network help us explain why the Medici rose to power during this period? So the course will bring together models not only from economics and sociology but also from computer science, physics, random graph theory and mathematics, statistics. And my aim is to provide a synthesis and an introduction to the very multi- interdisciplinary approaches of analyzing networks. It should give you a toolbox to go forward with and draw upon as you analyze model networks. And we'll study basic measures of networks, models of network formation, models of diffusion, learning, contagion. As well as how networks impact behaviors. And we'll be using some statistical techniques for analyzing networks. And I'll point out some important areas for new research as we go along. What sort of background do you need? Well, the course is going to assume that you're comfortable with matrix algebra, since coding and analyzing networks these days makes heavy use of matrices. We'll also be using basic concepts from probability and statistics and some light calculus. There'll be a little bit of game theories in the course but I'll make sure that will be self-contained. And you should feel pretty comfortable on a computer. We'll be exploring some network data as we go along. Now the course is going to run for about eight weeks of lectures and then a final exam. Each week, there'll be video lectures available as well as a problem set and some occasional data exercises. There'll be interactions with the forms where you can communicate with your fellow students. And people who complete the course with a high enough score in the problem sets and final will earn a certificate of completion. We'll begin the course soon and you can find updates on the timing on my website. So please tell at least two of your friends who might be interested in the course. Why at least two? Well, join the course to find out. Hope to see you again soon, take care.

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